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33c3 pre-roll music
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Herald: Err ...
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H: ... a talk would be good, right?
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applause
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Do you want to give a talk?
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Toni: Aah, it’s a little early[br]but I’ll try.
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Herald: Okay, guys, well, I found someone[br]who’s willing to give a talk!
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laughter and applause
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That is most excellent.[br]So, if you ever asked yourself,
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I’ve got this big regime and[br]I’m rolling out internet censorship,
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what does my economy do?
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There are people in here[br]asking that question, right?
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There’s always someone at Congress[br]who’s asking some question.
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Well, you came to the right place,[br]and as part of her PhD thesis work
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Toni is going answer that question,[br]hopefully, to a satisfactory point.
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Please give a warm round of applause![br]applause
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Toni![br]ongoing applause
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Toni: Okay, thanks everyone for being[br]here, I hope you can all hear me
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correctly. And I’m glad to be here[br]and to be presenting
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some part of my thesis to day.[br]Now, this is ongoing work
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so I’m really grateful for any kind of feedback[br]that you guys would have
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and I’m really only presenting this[br]as kind of a first try,
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because when I looked at the topic[br]of internet censorship
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and what that could mean for an economy,[br]I really didn’t find anything academic
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and I was quite surprised: it seemed[br]like a very obvious question to me,
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because I was looking mostly[br]at China at the beginning.
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And I read a lot of newspaper articles[br]and I talked to a lot of businessmen
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who told me: “Well, doing business[br]in China is very difficult”
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and I think China is really[br]holding itself back by having
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this big censorship thing going.
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But no one really looked into[br]how it is holding itself back
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or if it is even holding itself back.
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So there is really[br]very, very little research.
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And we don’t even have an agreement among[br]economists or business studies people
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about what impact the internet has[br]on the economy. So if you want to ask:
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“So what does internet censorship do[br]to an economy?” it seems pretty obvious
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to first ask: “What does the internet do to[br]an economy?” and we don’t even know that.
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That was quite surprising to me and I’m[br]going to be talking about the reasons
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for that a little bit later on. But in[br]general, I was thinking of a research
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question to ask which for me is: “Does[br]internet censorship reduce economic welfare?”
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Now, not all of you are economists,[br]so some of you might think of welfare
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more as the transfer payments[br]that a state gives to its poorer people.
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But for economists, economic welfare[br]is defined as the consumer
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and producer surplus. So basically, the[br]difference between what something costs
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and what you can sell it for[br]is the producer surplus.
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The difference between[br]what you would be willing to pay
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and what you’re actually paying[br]is your consumer surplus.
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Now let’s assume I have a laptop[br]and I bought this.
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And I would have been willing to pay[br]€ 1500 for this laptop because
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I think it’s a very good product,[br]it’s by Lenovo that makes good laptops.
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But actually I got it for like €800[br]or €900. That would mean
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my personal consumer surplus[br]is something like €600 or €700.
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And if we add up everyone’s[br]individual consumer surplus
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we get the economic welfare surplus.
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So first, I was trying to figure out[br]what does the internet mean
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for the economy. And I’ve said that there[br]is really no good agreement on that.
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Now, a very crude measure that I found is[br]how much does "the Internet economy"
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contribute to GDP?[br]Now, what is "the internet economy"?
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It wasn’t very clear in the research[br]that I’ve read. It seems to be sort of
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online retail, and possibly some other[br]internet-enabled services?
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Possibly but not necessarily[br]internet advertisement revenue
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is reflected in this. But because it was[br]BCG, which is a big consulting agency
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that basically published this research[br]they weren’t very diligent about
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their methods, basically.[br]So we can see, well it seems that the UK
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has a pretty big part of internet economy[br]as part of GDP.
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That’s probably mostly because of[br]online retail which is bigger in the UK
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than in most other countries we look at.[br]And we see that there is
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a small difference between[br]developed and developing market averages
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when looking only at the G20 countries.[br]But this seems like a very
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dissatisfactory answer because first[br]of all, I don’t know the methods,
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so I can’t really say[br]whether this is actually good.
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And secondly, GDP is actually[br]not a good measure
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for what we are trying to measure because[br]a lot of the stuff that the internet creates,
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a lot of the value the internet creates[br]isn’t captured by GDP at all.
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One example is free online courses.[br]Most of the online courses you can take
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on the web are actually free.[br]And most of them are not ad-enabled.
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So most of them don’t really have[br]advertisements in the general sense.
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So classical economics basically says:[br]“Well, they don’t really create any value.”
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But if you’ve ever taken[br]one of these online courses,
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and maybe you’ve been lucky[br]and took a good one
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you would actually… I would say that[br]some of the courses I took,
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they created some value for me.[br]So one of the ways to look at this
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is actually to think about time as[br]something that has opportunity cost.
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So if I’m spending my time doing this[br]online course I’m not spending it
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e.g. earning money. I’m also not[br]spending it doing something leisurely
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that is fun for me.[br]And these guys, Brynjolfsson
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– I’m sorry I don’t know[br]how to pronounce it exactly,
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he sounds Swedish, possibly –[br]and ohh, in 2012
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they tried to get an idea of[br]how much consumer surplus
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these online courses actually create.[br]Which isn’t at all
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reflected in the GDP.[br]And you see that in some models
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it would be 5% of GDP[br]for these online courses alone.
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Even if we take their more... most conservative[br]model which is $4.18 billion
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on average for the years 2008-2011,
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that’s still a pretty significant chunk[br]of economic welfare
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that’s somehow being created[br]that is not reflected in GDP
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because GDP is only stuff[br]that you actually pay money for.
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Another example that we[br]might think of is Wikipedia.
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Now Wikipedia has a certain cost of[br]operating: obviously the servers and stuff.
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But because most people contributing[br]to Wikipedia are actually volunteers
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the cost of operating[br]does not really reflect
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the true value Wikipedia creates.[br]And one of the…
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even if you don’t want to say…[br]even if you don’t agree
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that time has opportunity cost, what[br]about the money that you don’t spend
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on encyclopedias? How many of you guys[br]have encyclopedias at home?
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OK, that’s more than I expected!
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How many of you guys have[br]recent encyclopedias at home?
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That’s a little less, this is kind of more[br]what I was expecting.
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And now, my family also… we also have[br]an encyclopedia at home.
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I think it’s from 1985 or something.[br]And before this encyclopedia
0:08:02.720,0:08:06.210
we would regularly update an encyclopedia,[br]we would regularly go out and buy
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a new encyclopedia because[br]knowledge changed, obviously.
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But ever since probably 1990,[br]we just didn’t bother.
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So, assuming an encyclopedia might,[br]like a physical book, might cost €100.
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And assuming sort of 2/3[br]of all households in Germany
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have had an encyclopedia at one point.
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We’re looking at 13 million households[br]at this point.
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Now you don’t buy an encyclopedia[br]every year but you might buy it
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every ten years. So in order to simplify[br]this we can say, every year
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1.3 million households buy[br]an encyclopedia on average.
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1.3 million times €100,[br]so we’re at €130 million
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of economic welfare, of something that[br]people were willing to spend money for
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that they’re not spending money for anymore[br]because of Wikipedia, because now that
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we have Wikipedia most of the encyclopedias[br]aren’t actually useful for us anymore
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because the knowledge that we have,[br]the knowledge that they would have
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would be outdated very, very soon and[br]Wikipedia tends to be more up to date.
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Well, that was from the consumer’s side.[br]But what about the business side?
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There’s a lot of research on whether the[br]internet actually increases productivity
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for businesses or not. Well, I don’t really[br]want to go into that debate because
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it’s a really long tedious debate that is[br]kind of focused on “Well, you did this
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method wrong”, or “You did this wrong”,[br]and “Well, I don’t think your argument
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makes sense”. So it’s very… I don’t like[br]this kind of debate. I really like to go
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deeper in things. But one of the things[br]that I found was that a lot of businesses
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do rely on the internet by now. Now[br]we can see on this graph that most firms,
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overall about 70% of firms actually[br]use the email to communicate.
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Now email obviously only works[br]if you have internet, so they need
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some sort of access to internet in order[br]for their current business model to work.
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Now this was just some short ideas on[br]sort of what can the internet mean for
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the economy. And now I want to talk about[br]Internet censorship, just a little bit.
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Now, I’m not a censorship expert. I’m just[br]someone who read a lot of papers about it,
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and who was very interested in what kind[br]of effects this has beyond sort of
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the obvious “people don’t have access[br]to political information”.
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So first a definition. ‘Internet censorship’[br]is the controller suppression
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of what can be accessed, published[br]or viewed on the Internet
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enacted by regulators or on their own[br]initiative. Now, in trying to conceptualize
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internet censorship, for me, personally,[br]there’s two dimensions that are
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very important. One is how targeted[br]is this internet censorship?
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Now, you could, in theory, basically[br]have internet censorship
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that is very, very targeted,[br]which you see in some cases.
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Or you can have censorship[br]that isn’t targeted at all, like in Egypt.
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They just decided to close the internet[br]down, basically, for a day.
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That isn’t very targeted censorship,[br]obviously. The other thing to look at
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is how widespread is it? So if you are[br]a business or if you’re a normal consumer
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how probable is it that you would come (?)[br]something that’s censored?
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Now, obviously, if you’re in China it’s[br]a lot more probable that you would
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try to access something that’s censored[br]than if you’re in Germany. Even though
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Germany also does some censorship.[br]And the way I like to conceptualize it is
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to be kind of on a continuum. So I don’t[br]look… I don’t say “Well, either
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there’s censorship or there isn’t[br]censorship”. What I’m trying to say is
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“Censorship has a big spectrum[br]of things that can happen”.
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These are some types of Internet censorship[br]that have different sort of implications.
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I don’t want to go through them in detail[br]because I think we’ve heard some really
0:12:16.309,0:12:21.540
interesting talks on Internet censorship[br]already. But this is kind of
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interesting or important for the model[br]that I’m trying to build.
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But before trying to build my model,[br]first some more motivation.
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I was trying to look at “is there any[br]evidence that it would have
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an economic impact?”. And there actually[br]is a study that’s conducted by sort of
0:12:39.819,0:12:45.819
lobbying organizations, so obviously[br]should be taken with a grain of salt.
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But it is quite interesting, and it shows[br]that there seems to be a correlation
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between freedom and how good[br]the economic impact of internet is.
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This is just a simple correlation. You can[br]see that there’s a really good line
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going through it. They did do some[br]controlling for GDP per capita, so
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for development level. But it still seems[br]quite rudimentary, to be honest.
0:13:16.580,0:13:23.979
The data that they use is quite bad[br]because it is very, very…
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it’s just not finally granular enough, and[br]a lot of it is kind of… someone rating…
0:13:30.289,0:13:34.809
so “How do you think the economic…”,[br]“How do you think Internet
0:13:34.809,0:13:39.699
impacts the economy in this country?”[br]And then this is the data that they use,
0:13:39.699,0:13:48.069
to some degree. So it seemed very…[br]it didn’t really seem like a good, final answer.
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So I’m trying to set up my own model.[br]And in my model I have a government
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that chooses the type of censorship. And[br]for this type of censorship that it chooses
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it pays a cost. Because we all know[br]censorship can be very expensive.
0:14:02.509,0:14:09.709
And in my model for now the only type of[br]expenses that I calculate are actual
0:14:09.709,0:14:16.989
manpower and technology expenses. I don’t[br]calculate reputation expenses at this point.
0:14:16.989,0:14:24.209
There is… there are firms in n industries.[br]Now this n is kind of not a fixed number
0:14:24.209,0:14:30.629
but instead is a number that can fluctuate[br]depending on the kind of country
0:14:30.629,0:14:37.879
I’m trying to model. And these industries[br]distinguish themselves by their
0:14:37.879,0:14:42.459
information intensity, or what I like[br]to call ‘information intensity’. Basically
0:14:42.459,0:14:47.540
I look at information as a commodity.[br]And what I’m trying to decide, or
0:14:47.540,0:14:51.910
the way I distinguish different kinds of[br]industry is how important is information
0:14:51.910,0:14:56.279
as a commodity, as opposed to other kinds[br]of commodities that are important
0:14:56.279,0:15:01.160
for this industry. So let’s look at[br]information intensity equals Zero.
0:15:01.160,0:15:05.259
Like if we don’t really… if information[br]as a commodity really isn’t important,
0:15:05.259,0:15:09.720
especially sort of conveyed information,[br]transmitted information. We can
0:15:09.720,0:15:14.309
think of traditional agriculture. Now[br]I know today’s agriculture tends to be
0:15:14.309,0:15:18.859
large-scale, and there’s a lot of[br]technology involved. But if you look at
0:15:18.859,0:15:24.170
very traditional agriculture that we[br]still might see happening in some parts
0:15:24.170,0:15:30.060
of Africa there usually is very, very[br]little information transmission involved.
0:15:30.060,0:15:34.069
And most of the information transmission[br]that is involved is actually mostly through
0:15:34.069,0:15:40.189
word of mouth. So that would be a case of[br]information intensity of very close to Zero.
0:15:40.189,0:15:43.790
And then if we look at information intensity[br]of 1 where basically the internet is
0:15:43.790,0:15:48.759
the most… or information is the most[br]important commodity. Internet businesses
0:15:48.759,0:15:54.839
themselves would… obviously qualify here,[br]– sorry – like, let’s look at Facebook
0:15:54.839,0:15:59.899
and other kinds of businesses like this.[br]And in between we have sort of industrial
0:15:59.899,0:16:03.339
companies in the modern world.[br]Now if we’re closer to the Zero end
0:16:03.339,0:16:07.639
of the spectrum we might be[br]at 0.2 .. 0.3, something like this,
0:16:07.639,0:16:15.449
we might be in traditional garment[br]factories. They do have information needs,
0:16:15.449,0:16:20.720
they get their cuts and stuff from the[br]Internet by now, or by email.
0:16:20.720,0:16:25.129
But once they have them they basically stay[br]the same for a couple of weeks or months.
0:16:25.129,0:16:30.409
So there’s a very low information[br]requirement. On the other side,
0:16:30.409,0:16:35.999
closer to 0.8 or something[br]like that we have high-tech,
0:16:35.999,0:16:41.220
especially software manufacturing,[br]so to speak. Information and being able
0:16:41.220,0:16:44.930
to transmit this information is very[br]important. Now, in between we might look
0:16:44.930,0:16:51.259
at traditional industrial companies[br]like automobile manufacturing
0:16:51.259,0:16:56.000
that might be somewhere in between.[br]And before the game, or before…
0:16:56.000,0:17:00.160
or at the first run of the model[br]‘service level’ and ‘globalization level’
0:17:00.160,0:17:05.599
are randomly distributed. The information[br]intensity of industries is also kind of
0:17:05.599,0:17:11.799
randomly distributed, but not in a true[br]random fashion. Because when looking
0:17:11.799,0:17:15.500
in the wild, sort of what kind of[br]economies exist, most of them…
0:17:15.500,0:17:19.199
the information intensity of one[br]industry is kind of correlated with
0:17:19.199,0:17:23.449
information intensities of other industries[br]in this country. Like in Germany
0:17:23.449,0:17:29.269
we’re very known for a certain type[br]of industry that we have quite a lot of,
0:17:29.269,0:17:35.440
which is manufacturing, very high-technology[br]manufacturing. So we have more industries
0:17:35.440,0:17:40.450
in this area but we have less traditional[br]agriculture, for example.
0:17:40.450,0:17:44.669
So having a true random distribution[br]wouldn’t work. In addition the service level
0:17:44.669,0:17:49.919
and the globalization level are randomly[br]distributed as kind of external variables.
0:17:49.919,0:17:55.090
Obviously, this is a simplification because[br]I can’t really start at the beginning like
0:17:55.090,0:17:58.870
I can’t say: “Oh well, I’ll start,[br]I don’t know, 2000 BC
0:17:58.870,0:18:04.190
with a very blank economy, and then[br]something happens and something happens
0:18:04.190,0:18:08.320
and something happens”. That’s just not[br]realistic. So in order to get a better idea
0:18:08.320,0:18:12.830
of what happens with different types of[br]economies, what I’m doing is I’m running
0:18:12.830,0:18:18.899
this game or this model again and again.[br]And having these random parameters
0:18:18.899,0:18:24.539
basically changed everytime.[br]So on average there should be…
0:18:24.539,0:18:29.289
there should be usable results.
0:18:29.289,0:18:35.230
Now what this is actually missing[br]is the consumer as a labourer.
0:18:35.230,0:18:40.090
So I don’t really have ‘labour’ reflected[br]in here. A more complete model would have
0:18:40.090,0:18:44.080
that reflected. But it’s not the most[br]interesting aspect of my model, so
0:18:44.080,0:18:49.940
I’m not presenting this here, basically.
0:18:49.940,0:18:56.080
Now, let’s look at what this would[br]mean for firms. In my model
0:18:56.080,0:18:59.649
what kind of things would I expect[br]thinking through it logically which is
0:18:59.649,0:19:04.820
always the first step when trying to model[br]something. First of all if we have
0:19:04.820,0:19:10.130
an information intensity of something[br]greater than Zero but smaller than One.
0:19:10.130,0:19:14.410
Because the information intensity being[br]close to One is kind of a special case
0:19:14.410,0:19:18.520
that I’ll be talking about later on.[br]Internet censorship increases the cost
0:19:18.520,0:19:22.360
and uncertainty of information.[br]And of course that is more important
0:19:22.360,0:19:27.850
the more important information is[br]for this certain industry.
0:19:27.850,0:19:33.850
So for a traditional garment factory[br]internet censorship might be a lot
0:19:33.850,0:19:41.000
less important than for a semiconductor[br]factory that has to receive
0:19:41.000,0:19:47.090
new blueprints every day or every month[br]or something. The second thing is
0:19:47.090,0:19:51.559
the more globalized the economy as a whole[br]is the more costly internet censorship
0:19:51.559,0:19:58.490
will be. Similar reasoning.
0:19:58.490,0:20:02.990
And another thing for firms is the[br]less focused the censorship
0:20:02.990,0:20:07.640
the higher the cost. Now this assumes that[br]the censorship or the goal of censorship
0:20:07.640,0:20:14.370
usually isn’t to turn down firms or to[br]make sure that firms don’t succeed.
0:20:14.370,0:20:19.820
So if censorship is very focused[br]firms tend to be affected less
0:20:19.820,0:20:25.149
which makes their associated cost less.[br]Now of course we can argue, well,
0:20:25.149,0:20:29.399
firms can circumvent censorship, and they[br]can do that for sure. But it is expensive
0:20:29.399,0:20:35.299
to do that. If you’ve ever tried a VPN[br]in China e.g., first, buying the VPN
0:20:35.299,0:20:40.919
is expensive. Then, having someone sort of[br]make sure that the VPN works is expensive,
0:20:40.919,0:20:44.009
every couple of months you need to change[br]it because the Chinese Government decides,
0:20:44.009,0:20:52.549
well, this VPN shouldn’t work anymore. So[br]it’s a very expensive and uncertain thing,
0:20:52.549,0:20:57.909
really. For firms in[br]‘information intensity = 1’
0:20:57.909,0:21:02.940
it obviously also increases the cost[br]of operating. Some of these firms actually
0:21:02.940,0:21:07.970
carry out some censorship for governments.[br]We have seen that happening more recently.
0:21:07.970,0:21:12.570
But there might actually be some firms[br]that have a relative advantage, especially
0:21:12.570,0:21:16.820
domestic firms often have a relative[br]advantage due to the censorship because
0:21:16.820,0:21:20.950
they know the regulators better, they know[br]how to deal with it, they might have
0:21:20.950,0:21:25.039
less need to circumvent, actually.[br]And even if they do need to circumvent
0:21:25.039,0:21:29.539
it’s easier for them because[br]they speak the language etc.
0:21:29.539,0:21:34.090
This is actually a special case that I’ll[br]be talking about a little bit later as well.
0:21:34.090,0:21:38.460
For the government – I’ve said[br]that censorship is costly. But moreover,
0:21:38.460,0:21:43.100
the more targeted and accurate censorship[br]is the more manpower and technology intensive
0:21:43.100,0:21:50.389
it actually is. This is a finding by[br]Leberknight et al. in a research paper.
0:21:50.389,0:21:54.480
I think they’re electrical engineers, and[br]they calculated through different types
0:21:54.480,0:22:00.350
of censorships and how expensive it would[br]be to scale them up. So that is actually
0:22:00.350,0:22:03.479
a really interesting finding because[br]it shows that for governments
0:22:03.479,0:22:10.460
having sort of less targeted censorship[br]is less costly. But this is the kind of
0:22:10.460,0:22:17.039
censorship that is actually most affecting[br]in a negative way to firms,
0:22:17.039,0:22:20.990
in an economy. So that’s kind of not[br]a result that we would really want
0:22:20.990,0:22:24.919
because the incentives don’t line up in[br]that way. And economists love to talk
0:22:24.919,0:22:29.169
about incentives, obviously. Now for[br]consumers, they would obviously get
0:22:29.169,0:22:33.090
less benefits through the internet, the[br]benefits that I’ve talked about before.
0:22:33.090,0:22:38.430
And also businesses often pass on the cost[br]to consumers.
0:22:38.430,0:22:43.350
Now however, some countries[br]still benefit from internet censorship.
0:22:43.350,0:22:45.970
I’ve talked mostly [br]about why it’s costly to do it,
0:22:45.970,0:22:48.700
and I think it is costly in most cases.
0:22:48.700,0:22:53.210
But developing countries that start out at[br]low service and low globalization levels
0:22:53.210,0:22:58.950
usually have… in these kind of situations[br]internet censorship has less of an impact,
0:22:58.950,0:23:04.370
less of a negative impact.[br]And censorship can actually act
0:23:04.370,0:23:08.880
as protectionism. In information intensive[br]industries governments can use this kind
0:23:08.880,0:23:13.650
of censorship to push domestic industries[br]and enable catch-up growth. Now there
0:23:13.650,0:23:16.820
are a couple of further prerequisites.[br]First of all, the country needs to be
0:23:16.820,0:23:20.640
large enough so that these [br]information intensive industries
0:23:20.640,0:23:23.640
have a domestic market as well.
0:23:23.640,0:23:27.379
Obviously. And then also only[br]targeted censorship can serve as
0:23:27.379,0:23:32.159
protectionism. The only other way would be[br]if you decided on a domestic intranet and
0:23:32.159,0:23:38.059
basically closed your entire intranet off[br]to the world. Which is kind of difficult.
0:23:38.059,0:23:41.850
But what about the long-term effects[br]of that? Would they still be positive
0:23:41.850,0:23:47.669
for the government? Now, I’m using[br]‘positive’ in a very… sort of something
0:23:47.669,0:23:51.820
that should be taken with a grain of salt,[br]obviously. And what I did is I looked
0:23:51.820,0:23:57.330
at China. Obviously, I’m a China watcher.[br]So I’m really interested in China. And
0:23:57.330,0:24:02.190
this is kind of where my interest started.[br]And I’m really trying to find a framework
0:24:02.190,0:24:07.219
where China isn’t the exception but[br]instead China kind of fits into the model.
0:24:07.219,0:24:13.129
What we see is the Chinese government has[br]outsourced much if its censorship to these
0:24:13.129,0:24:19.000
internet companies. Baidu, Sina weibo,[br]Tencent probably would not exist by now,
0:24:19.000,0:24:24.820
actually, if the censorship didn’t exist.[br]And what we actually see now is that
0:24:24.820,0:24:29.750
WeChat e.g. is going global. It has[br]more functionality than Whatsapp
0:24:29.750,0:24:35.799
and they’re trying to get out. But as I’ll[br]be talking about later on a little bit
0:24:35.799,0:24:41.810
the censorship is starting to be a problem[br]for these companies that used to benefit.
0:24:41.810,0:24:46.840
There’s some things about Chinese… about[br]the character of Chinese Internet censorship
0:24:46.840,0:24:54.409
that is relevant here. But what about[br]the future? Now first it’s difficult to
0:24:54.409,0:24:58.660
innovate with this kind of censorship. And[br]this kind of insular education that we see
0:24:58.660,0:25:03.450
also makes innovation, real innovation,[br]very difficult. In China e.g. Github
0:25:03.450,0:25:07.631
is blocked most of the time. That makes[br]kind of collaborating, especially in
0:25:07.631,0:25:11.730
coding environments, very, very hard.[br]
0:25:11.730,0:25:14.490
Second, we see more global internet enabled
0:25:14.490,0:25:20.059
supply chains in the world. So if we have[br]these global Internet-enabled supply chains
0:25:20.059,0:25:25.669
having internet censorship turns out to be[br]more of a disadvantage the more globalized
0:25:25.669,0:25:31.879
these supply chains actually become. And[br]information becomes the most important
0:25:31.879,0:25:36.230
commodity all throughout China. Now this[br]of course also makes Internet censorship
0:25:36.230,0:25:41.000
more costly for the economy. What about[br]possible positives? So what could work
0:25:41.000,0:25:45.500
in the Chinese government’s favour? First,[br]the Chinese intranet is actually pretty
0:25:45.500,0:25:50.429
attractive to most people. Most people[br]don’t try to go outside, even like
0:25:50.429,0:25:55.269
they don’t even know that they can’t. They[br]just don’t want to do it. Second, the IoT,
0:25:55.269,0:25:59.429
where machines communicate with each other[br]doesn’t need to be affected because
0:25:59.429,0:26:04.820
most of the censorship that we see[br]happening could be reworked in a way
0:26:04.820,0:26:08.599
that doesn’t affect machine-to-machine[br]communication. And that wouldn’t be
0:26:08.599,0:26:14.039
a problem for what the censorship intends[br]to do which is sort of suppress political
0:26:14.039,0:26:20.669
opposition. And a third, the government[br]wants an economy more focused on domestic
0:26:20.669,0:26:24.230
consumption. So if they want to do this[br]then censorship might actually be good
0:26:24.230,0:26:30.669
for that. Now, for me, what I found out[br]when doing this research is first,
0:26:30.669,0:26:34.709
standard economic models really aren’t[br]suited for this kind of question. Because
0:26:34.709,0:26:38.370
they tend to use GDP, and I’ve told you[br]why GDP really is not a good measure
0:26:38.370,0:26:43.419
for that. Second, the next step that[br]I’ll be doing is agent-based modeling.
0:26:43.419,0:26:48.910
But I would really like to feed my models[br]with some reliable data. And I can’t
0:26:48.910,0:26:53.400
really find any of that. I can find some[br]data going back a couple of years
0:26:53.400,0:26:57.779
on, like, is there censorship, is there[br]no censorship. But I can’t really find any
0:26:57.779,0:27:02.150
good data that distinguishes between[br]different types of censorship, which would
0:27:02.150,0:27:06.440
be really important for the kind of[br]research that I really want to carry out
0:27:06.440,0:27:11.610
in the future. Thank you, guys. If you[br]have questions you can ask now or
0:27:11.610,0:27:15.129
you can come to me later, you can[br]of course also send me an e-mail.
0:27:15.129,0:27:18.719
I’m always happy to talk about this topic.
0:27:18.719,0:27:27.529
applause
0:27:27.529,0:27:32.000
Herald: Thank you very much for this talk.[br]We have six microphones at the floor level
0:27:32.000,0:27:35.660
here, so if you have questions we have[br]a very brief amount of time.
0:27:35.660,0:27:40.430
Please line up at the microphones.[br]We have microphone no. 2 over here.
0:27:40.430,0:27:46.480
Question: I want to mention one thing.[br]Always when talking about China censorship
0:27:46.480,0:27:51.299
this censorship applies to China main[br]land. So it’s not Hong Kong and not Taiwan.
0:27:51.299,0:27:51.959
Toni: Yes.
0:27:51.959,0:27:55.769
Question: And my question I want [br]to ask is:
0:27:55.769,0:27:59.219
What do you think about productivity [br]of work?
0:27:59.219,0:28:05.200
So e.g. if you shut down Facebook do you[br]think this would increase working
0:28:05.200,0:28:08.059
productivity?[br]Toni laughs
0:28:08.059,0:28:13.010
applause[br]Toni: That’s a really interesting question,
0:28:13.010,0:28:16.470
and something that I haven’t seen anywhere[br]in literature. There is a big literature
0:28:16.470,0:28:21.970
discussion about what the internet as such[br]means for productivity, and that’s
0:28:21.970,0:28:26.820
kind of both ways. Now, one of the things[br]to look at is that just because you
0:28:26.820,0:28:31.200
shut down Facebook doesn’t mean you[br]shut down any sort of social network.
0:28:31.200,0:28:36.389
And I do think that if people use Facebook[br]and suddenly aren’t able to use it anymore
0:28:36.389,0:28:40.769
they would probably spend their resources[br]trying to find new ways to access Facebook
0:28:40.769,0:28:48.790
which would probably not exactly[br]improve their productivity.
0:28:48.790,0:28:52.299
Herald: Next question[br]from microphone no. 2.
0:28:52.299,0:28:57.909
Question: Would it make sense to have[br]a model where firms use information
0:28:57.909,0:29:02.480
as an input to a production function and[br]then model censorship as a kind of tax
0:29:02.480,0:29:08.109
on that. That will seem like standard new[br]classical micro-econ one-on-one stuff?
0:29:08.109,0:29:12.390
Toni: That would make sense. I’ve actually[br]looked at this. One of the problems with
0:29:12.390,0:29:17.730
doing that is that information [br]as a commodity
0:29:17.730,0:29:23.350
is very difficult to be used in this new[br]classical way because you usually assume
0:29:23.350,0:29:28.020
that everything is kind of friction-less.[br]And if things are friction-less then
0:29:28.020,0:29:31.619
information can’t really be a commodity[br]because you assume that information
0:29:31.619,0:29:36.500
basically gets transferred immediately,[br]and without any sort of censorship. So
0:29:36.500,0:29:39.590
we can talk about this a little bit later.[br]Maybe you have some ideas that
0:29:39.590,0:29:43.740
I haven’t found yet.[br]It would be interesting.
0:29:43.740,0:29:47.539
Herald: And the next question,[br]as well, from microphone no. 2.
0:29:47.539,0:29:53.629
Question: So, going the same direction:[br]for GDP is rather defined what is
0:29:53.629,0:29:59.429
the optimization problem for a government.[br]For your further approaches what would be
0:29:59.429,0:30:05.279
the optimization that a government like[br]China does then. If you say e.g. Wikipedia
0:30:05.279,0:30:08.950
which leaks out to all over the world but[br]what is the government optimizing then?
0:30:08.950,0:30:15.049
Toni: What I’m looking at is economic welfare[br]as defined as producer and consumer surplus.
0:30:15.049,0:30:22.539
And I assume that the government’s goal[br]is to optimize economic welfare for both
0:30:22.539,0:30:27.519
producers, consumers and also for itself[br]as a producer and as a consumer.
0:30:27.519,0:30:32.240
Question: So your criticism is more like[br]you don’t have a good proxy,
0:30:32.240,0:30:33.870
using GDP for economic welfare?
0:30:33.870,0:30:36.870
Toni: Yes, yes.[br]Okay. Thank you.
0:30:36.870,0:30:38.370
Herald: I’m afraid we’re all out of time.
0:30:38.370,0:30:40.350
Please give a warm round[br]of applause to Toni!
0:30:40.350,0:30:43.690
applause
0:30:43.690,0:30:46.260
post-roll music
0:30:46.260,0:30:50.540
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